Abstract
Introduction:
Artificial Intelligence (AI) offers great potential for transforming healthcare delivery leading to better patient-outcomes and more efficient care delivery. However, despite these advantages, integration of AI in healthcare has not kept pace with technological advancements. Previous research indicates the importance of understanding various organisational factors that shape integration of new technologies in healthcare. Therefore, the aim of this study is to provide an overview of the existing organisational factors influencing adoption of AI in healthcare from the perspectives of different relevant stakeholders. By conducting this review, the various organisational factors that facilitate or hinder AI implementation in healthcare could be identified.
Methods and analysis:
This study will follow the Joanna Briggs Institute framework, which includes the following stages: (1) defining and aligning objectives and questions, (2) developing and aligning the inclusions criteria with objectives and questions, (3) describing the planned approach to evidence searching and selection, (4) searching for the evidence, (5) selecting the evidence, (6) extracting the evidence, (7) charting the evidence, and summarising the evidence with regard to the objectives and questions.
The databases searched will be MEDLINE (Ovid), CINAHL (Plus), PubMed, Cohrane Library, Scopus, MathSciNet, NICE Evidence, OpenGrey, O’REILLY, and Social Care Online from January 2000 to June 2021. Search results will be reported based on The Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews guidelines. The review will adopt Diffusion of Innovations theory, Technology Acceptance Model, and Stakeholder theory as guiding conceptual models. Narrative synthesis will be used to integrate the findings.
Ethics and dissemination:
Ethics approval will not be sought for this scoping review as it only includes information from previously published studies. The results will be disseminated through publication in a peer-reviewed journal. In addition, to ensure its findings reach relevant stakeholders, they will be presented at relevant conferences.
Artificial Intelligence (AI) offers great potential for transforming healthcare delivery leading to better patient-outcomes and more efficient care delivery. However, despite these advantages, integration of AI in healthcare has not kept pace with technological advancements. Previous research indicates the importance of understanding various organisational factors that shape integration of new technologies in healthcare. Therefore, the aim of this study is to provide an overview of the existing organisational factors influencing adoption of AI in healthcare from the perspectives of different relevant stakeholders. By conducting this review, the various organisational factors that facilitate or hinder AI implementation in healthcare could be identified.
Methods and analysis:
This study will follow the Joanna Briggs Institute framework, which includes the following stages: (1) defining and aligning objectives and questions, (2) developing and aligning the inclusions criteria with objectives and questions, (3) describing the planned approach to evidence searching and selection, (4) searching for the evidence, (5) selecting the evidence, (6) extracting the evidence, (7) charting the evidence, and summarising the evidence with regard to the objectives and questions.
The databases searched will be MEDLINE (Ovid), CINAHL (Plus), PubMed, Cohrane Library, Scopus, MathSciNet, NICE Evidence, OpenGrey, O’REILLY, and Social Care Online from January 2000 to June 2021. Search results will be reported based on The Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews guidelines. The review will adopt Diffusion of Innovations theory, Technology Acceptance Model, and Stakeholder theory as guiding conceptual models. Narrative synthesis will be used to integrate the findings.
Ethics and dissemination:
Ethics approval will not be sought for this scoping review as it only includes information from previously published studies. The results will be disseminated through publication in a peer-reviewed journal. In addition, to ensure its findings reach relevant stakeholders, they will be presented at relevant conferences.
| Original language | English |
|---|---|
| Article number | e044074 |
| Number of pages | 6 |
| Journal | BMJ Open |
| Volume | 11 |
| Issue number | 3 |
| Early online date | 22 Mar 2021 |
| DOIs | |
| Publication status | E-pub ahead of print - 22 Mar 2021 |
Keywords
- Artificial intelligence
- Health Services
- innovation adoption